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This study aims to provide a comprehensive review and bibliometric analysis of the literature in the field of science, technology, engineering and mathematics (STEM) education over the past 15 years, with a specific focus on global distribution and research trends.

This study collected 1,718 documents from the Web of Science (WOS) database and analyzed their timeline distribution, geographical distribution, research topics, subject areas, learning stages and citation burst using a bibliometric approach with VOSviewer and Citespace.

Results indicated that: overall, STEM education has increasingly gained scholarly attention and is developing diversely by emphasizing interdisciplinary, cross-domain and regional collaboration. In terms of global collaboration, a collaborative network with the USA in the center is gradually expanding to a global scope. In terms of research themes, four key topics can be outlined including educational equity, pedagogy, empirical effects and career development. Social, cultural and economic factors influence the way STEM education is implemented across different countries. The developed Western countries highlighted educational equity and disciplinary integration, while the developing countries tend to focus more on pedagogical practices. As for research trends, eastern countries are emphasizing humanistic leadership and cultural integration in STEM education; in terms of teachers’ professional development, teachers’ abilities of interdisciplinary integration, technology adoption and pedagogy application are of the greatest importance. With regards to pedagogy, the main focus is for developing students’ higher-order abilities. In terms of education equity, issues of gender and ethnicity were still the hottest topics, while the unbalanced development of STEM education across regions needs further research.

This study provides a global landscape of STEM education along the timeline, which illustrates the yearly progressive development of STEM education and indicates the future trends.

Preservice teacher (PST) professional development programs are crucial for cultivating high-quality STEAM teachers of the future, significantly impacting the quality of regional STEAM education. The Guangdong-Hong Kong-Macao Greater Bay Area, as a region of cross-border cooperation, integrates the resources and advantages of Guangdong, Hong Kong, and Macao, possessing rich cultural heritage and innovative capabilities. Transdisciplinary Education for Cultural Inheritance (C-STEAM) is an effective approach to promoting educational collaboration within the Greater Bay Area, facilitating the integration of both technological and humanities education. This study aims to develop a Technology-Enabled University-School-Enterprise (T-USE) collaborative education model and implement it in the Greater Bay Area, to explore its role as a support mechanism in professional development and its impact on C-STEAM PSTs' professional capital.

Adopting a qualitative methodology, the study interviewed PSTs who participated in a C-STEAM teacher education course under the T-USE model. Thematic coding is used to analyze their knowledge acquisition, interaction benefits with community members, and autonomous thinking and decision-making in theoretical learning and teaching practice.

The findings show that the T-USE model significantly enhanced the PSTs' human capital, including teaching beliefs, knowledge, and skills. In terms of social capital, PSTs benefited from collaboration with PST groups, university teaching teams, in-service teachers, and enterprises, though challenges such as varying levels of expertise among in-service teachers and occasional technical instability emerged. For decisional capital, the T-USE model provided opportunities for autonomous thinking and promoted teaching judgment skills through real teaching challenges and scenarios. Reflective practice activities also supported PSTs' professional growth.

This study reveals the effectiveness and internal mechanism of the T-USE model in C-STEAM PST training, offering significant theoretical and practical references for future PST education.

Targeting public–private partnership (PPP) projects, the purpose of this paper is to help decision makers fairly allocate financial risk between governments and private investors through a properly designed length of concession period.

On the one hand, the length of the concession period should be long enough to help private investors to achieve their expected profits. On the other hand, the length of a concession period cannot be decided without agreeing on an upper limit, since an overlong concession period takes too much time for governments to recover their investment and leads to an overly lucrative condition for private investors. Following this logic, the concession period decision range is decided, which defines the lower and upper limits for the length of the concession period. The net present values (NPVs) for governments and private investors are estimated via Monte Carlo simulation to better reflect the uncertainties. To further decide on the optimal length of the concession period, the principle of fair risk allocation between governments and private investors is adopted. The concession period, as an important project parameter, should help to minimize the financial risk gap between governments and private investors.

The developed concession period determination process is validated using a numerical example of a PPP transportation project. The analysis outcomes show that the proposed methodology is capable of determining the length of the concession period so as to control private investors’ profit within a reasonable range while achieving a fair allocation of financial risk between governments and private investors. The outcomes also indicate that, before determining the optimal length for the concession period, governments may need to make a choice between better financial risk allocation or stringent profit control for private investors.

The determination process developed here may be inapplicable to social infrastructure PPPs where the income stream is less predictable. In addition, the data analysis targets a highway project with a capital subsidy provided by the government. To strengthen the effectiveness of the proposed determination process, further research should apply the model to PPPs with other kinds of government support.

The concession period for a PPP project is an important parameter and it is a common practice for governments to predetermine the length of the concession period before inviting tenders. The existing models for determining the concession period focus too much on the simulation of NPVs for project parties and neglect the importance of risk allocation in signing and maintaining a long-term contract. There is also a lack of research to evaluate the influence of governments’ preferences on the length of the concession period. To overcome the limitations of the existing models and enrich the methodology for concession period determination, this paper contributes to the body of knowledge by developing a concession period determination process which can help governments to make better decisions. The financial risk is expected to be more evenly shared between governments and private investors with the concession period derived from the proposed process. This determination process is also capable of evaluating the influence of governments’ preferences on the length of the concession period.

The growth in ageing population globally has led to the increase in demand for retirement or aged care homes. Adopting public–private partnership (PPP) in the global retirement village market has become the new approach to address some of the emerging challenges. This paper aims to explore and analyse the critical success factors (CSFs) for the adoption of PPP in the global retirement village market.

An empirical questionnaire survey was conducted with experienced practitioners in the global PPP and retirement village markets. Mean score analysis, normalization range method, Kendall’s coefficient of concordance and factor analysis were used for analysis.

Results show that out of the 27 CSFs identified, the most significant ones in developing PPP retirement village projects are “the age-friendly design of villages”, “appropriate location of PPP retirement village”, “reliable and accessible health and physical facilities” and “effective social inclusion and integration in villages”. Further analysis shows that the 27 CSFs can be grouped into 7 major factor groupings, namely, “effective project monitoring”, “financial support”, “social integration”, “effective contractual arrangement between parties”, “government commitment and support”, “sustainable design of village” and “effective payment structure”.

The outputs of this study will adequately inform retirement village developers, retirement village stakeholders and local government authorities of the best practices they should put in place to ensure the sustainable growth of the global retirement village market.